AI Solution Implementation ★★★ Expert Level
Enabling actual AI-driven business change is a major challenge. You need to identify and choose the right opportunities, create focus, align with stakeholders and ensure you have a solid business implementation plan in place.
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AI Solution Implementation

About the course

The AI solution implementation course is designed to build on previous analytical skills, focusing and enhancing them with clear steps, towards effective organizational implementation of AI solutions. Starting with the design, all the way to development and scaling. At the beginning of the course we introduce an implementation step-plan, which is designed to tackle the main value creation challenges throughout the process, and will guide us throughout the training. You will start by learning how to validate a business opportunity with basic analytics, followed by how to validate a proposed AI solution with a standardized approach. The goal is to ensure it solves the business problem at hand and is feasible in terms of business change, algorithmic approach and data requirements. Then, you will learn how to define the first version of the AI solution design and create focus, to ensure that this solution is quickly implementable, but still achieves impact. Next, you will learn how to build an implementation plan to ensure smooth business adoption. Finally, you will learn how to develop a test plan to enable a sharp feedback loop on the different solution components and translate its output to the next best improvements for your solution.  

Why this is for you

You have the skills to design an end-to-end solution and perhaps develop the solution from an analytical perspective, but you experience a challenge to ensure bottom-line value creation. You want to understand a structured approach to manage these challenges and ensure smooth implementation and organizational adoption. Taking part in an AI solution implementation team is a daunting task. It requires analytical skills, clear vision on the opportunities, the ability to define the solution's feasibility and having a clear methodology to further improve it. Once completed, this training will enable you to become an effective team member of an AI solution implementation team, focused on realistic implementable results and business adoption.  

For whom

This training is for Data Scientists, Data Engineers, and Business Professionals who have completed our AI solution design (1202) course.  

What you’ll learn

  1. The 5-phase AI solution implementation process and its pitfalls
  1. Validating an opportunity and a proposed AI solution
  2. Sharpening the scope for an MVP version of the AI solution, based on validation outcomes
  3. Building implementation and test plans to ensure rapid solution implementation and enabling of feedback cycle
  4. Reviewing MVP feedback loop and proposing relevant improvements, per AI solution component
  Learning Goals
  • AI solution development phases – explaining the differences between the AI solution development phases
  • AI solution validation – formulating validation questions on AI Solution design & translate to sharper scope
  • AI solution scope - challenging proposed AI Solution MVP-scope
  • AI solution development - preparing a successful implementation by creating test & implementation plans
  • AI solution improvement – translating feedback results to relevant improvement steps for AI solution
  Theory and practical use All trainings in the GAIn portfolio combine high-quality standardized training material with theory sessions from experts and hands-on experience where you directly apply the material to real-life cases. Each training is developed by top of the field practitioners which means they are full of industry examples along with practical challenges and know-how, fueling the interactive discussions during training. We believe this multi-level approach creates the ideal learning environment for participants to thrive.